code: def build_annotation(documents, annotations):
      for d, i in zip(documents, annotations):
          for w, c in zip(d, i):
              print("{}\t{}".format(w, c))
          print("")
  
file_path: nlp-architect/examples/chunker/inference.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import argparse
  import pickle
  from os import path
  import numpy
  from nlp_architect.models.chunker import SequenceChunker
  from nlp_architect.utils.generic import pad_sentences
  from nlp_architect.utils.io import check_size, validate_existing_filepath
  from nlp_architect.utils.text import SpacyInstance
label_desc: Use image node_id 2 for calling a global function with example usage: build_annotation(documents, annotations) without return types